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Articles | Volume XXXVIII-8/W20
https://doi.org/10.5194/isprsarchives-XXXVIII-8-W20-140-2011
https://doi.org/10.5194/isprsarchives-XXXVIII-8-W20-140-2011
31 Aug 2012
 | 31 Aug 2012

VULNERABILITY OF VEGETATION IN PARTS OF HIMALAYAS AND DYNAMIC GLOBAL VEGETATION MODELLING (DGVM) – STUDY USING VNIR AND THERMAL RESPONSES OF MODIS TIME SERIES DATA

G. S. Pujar, B. Harika, M. S. R. Murthy, and V. K. Dadhwal

Keywords: Multitemporal, Global-Environmental-Databases, Vegetation, Temperature, Modelling and Retrieval

Abstract. Vegetation responses to changing climate patterns need to be understood to devise adaptation strategy for a sustainable development, especially in the light of increasing climate related vulnerability. Dynamic Global Vegetation Models(DGVM) have the capacity and scope to develop understanding in this regard, due to their ability in simulating plant-vegetation-climate processes incorporating bioclimatic variables. However, prior to take up modelling using a spatially explicit DGVM, it may be imminent to prioritize the area for vulnerable contexts, so as to calibrate and validate the model optimally. Spatially explicit DGVMs require site level observations at canopy and leaf level/soil strata level for parametrization and implementation. Satellite data in VNIR and thermal regimes provide scope to understand the responses of various vegetation categories and enable to set up baseline addressing the foci of change as regions of vulnerability. Study carried out Western Himalayan transect using MODIS enhanced vegetation index and land surface temperature illustrates potential to differentiate areas that can be vulnerable due to warming trends disturbing cold to warm season energy level transition. Relations of these indices were studied in different vegetation categories and modelled spatially to derive potential vulnerable zones. Many sites showed high vulnerability while some sites showed distinct resilient behaviour by showing increase in EVI during warming periods. Potential zones were studied further using a spatially explicit Dynamic Global Vegetation Model for site level understanding. DGVM results in terms of biomass and carbon were studied to understand the trends in the vulnerable and resilient sites. Detailed characterisation of DGVM based modelling is underway to further diagnose the vulnerability contexts.